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<a href="_r_b_m_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment"> * </span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> *</span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> * \brief       -</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> *</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * \author      -</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * \date        -</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> *</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> *</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> * </span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * </span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * (at your option) any later version.</span></div>
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<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * </span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> *</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> */</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="preprocessor">#ifndef SHARK_UNSUPERVISED_RBM_RBM_H</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="preprocessor">#define SHARK_UNSUPERVISED_RBM_RBM_H</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span> </div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_model_8h.html">shark/Models/AbstractModel.h</a>&gt;</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="preprocessor">#include &lt;<a class="code" href="_energy_8h.html">shark/Unsupervised/RBM/Energy.h</a>&gt;</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#include &lt;shark/Unsupervised/RBM/Impl/AverageEnergyGradient.h&gt;</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span> </div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="preprocessor">#include &lt;sstream&gt;</span></div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;boost/serialization/string.hpp&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a>{</div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="comment"></span> </div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="comment">///\brief stub for the RBM class. at the moment it is just a holder of the parameter set and the Energy.</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> VisibleLayerT,<span class="keyword">class</span> H<span class="keywordtype">id</span>denLayerT, <span class="keyword">class</span> randomT&gt;</div>
<div class="foldopen" id="foldopen00043" data-start="{" data-end="};">
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html">   43</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_r_b_m.html" title="stub for the RBM class. at the moment it is just a holder of the parameter set and the Energy.">RBM</a> : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_model.html" title="Base class for all Models.">AbstractModel</a>&lt;RealVector, RealVector&gt;{</div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_model.html" title="Base class for all Models.">AbstractModel&lt;RealVector, RealVector&gt;</a> <a class="code hl_class" href="classshark_1_1_abstract_model.html">base_type</a>;</div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a1b20cbe042d3ac817fbf26c562e5b277">   47</a></span>    <span class="keyword">typedef</span> HiddenLayerT <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a1b20cbe042d3ac817fbf26c562e5b277" title="type of the hidden layer">HiddenType</a>; <span class="comment">///&lt; type of the hidden layer</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a5e271a43da1f3c33db74235402d7a84b">   48</a></span>    <span class="keyword">typedef</span> VisibleLayerT <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5e271a43da1f3c33db74235402d7a84b" title="type of the visible layer">VisibleType</a>; <span class="comment">///&lt; type of the visible layer</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a5b791282749a918b7894a9cb01c29a36">   49</a></span>    <span class="keyword">typedef</span> randomT <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5b791282749a918b7894a9cb01c29a36">randomType</a>;</div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a9e64a75e314d39c06b298f348f4edb27">   50</a></span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_energy.html" title="The Energy function determining the Gibbs distribution of an RBM.">Energy&lt;RBM&lt;VisibleType,HiddenType,randomT&gt;</a> &gt; <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a9e64a75e314d39c06b298f348f4edb27" title="Type of the energy function.">EnergyType</a>;<span class="comment">///&lt; Type of the energy function</span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a916086702525de4b9ccd1a715f4317d8">   51</a></span>    <span class="keyword">typedef</span> detail::AverageEnergyGradient&lt;RBM&gt; <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a916086702525de4b9ccd1a715f4317d8" title="Type of the gradient calculator.">GradientType</a>;<span class="comment">///&lt; Type of the gradient calculator</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span>    </div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">   53</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_model.html#a518304e95092673b7b6438cace052ef6" title="defines the batch type of the input type.">base_type::BatchInputType</a> <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">BatchInputType</a>;</div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">   54</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_model.html#aa0c72e230b9a1324c95ba8ac0b07ba13" title="defines the batch type of the output type">base_type::BatchOutputType</a> <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">BatchOutputType</a>;</div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span>    </div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="keyword">private</span>:<span class="comment"></span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">    /// \brief The weight matrix connecting hidden and visible layer.</span></div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment"></span>    RealMatrix m_weightMatrix;</div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment"></span> </div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">    ///The layer of hidden Neurons</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a1b20cbe042d3ac817fbf26c562e5b277" title="type of the hidden layer">HiddenType</a> m_hiddenNeurons;</div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment"></span> </div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">    ///The Layer of visible Neurons</span></div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5e271a43da1f3c33db74235402d7a84b" title="type of the visible layer">VisibleType</a> m_visibleNeurons;</div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span> </div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5b791282749a918b7894a9cb01c29a36">randomType</a>* mpe_rng;</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>    <span class="keywordtype">bool</span> m_forward;</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span>    <span class="keywordtype">bool</span> m_evalMean;</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span><span class="comment"></span> </div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span><span class="comment">    ///\brief Evaluates the input by propagating the visible input to the hidden neurons.</span></div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span><span class="comment">    ///@param patterns batch of states of visible units</span></div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span><span class="comment">    ///@param outputs batch of (expected) states of hidden units</span></div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span><span class="comment"></span>    <span class="keywordtype">void</span> evalForward(<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">BatchInputType</a> <span class="keyword">const</span>&amp; state,<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">BatchOutputType</a>&amp; output)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>        std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>=state.size1();</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span>        <span class="keyword">typename</span> HiddenType::StatisticsBatch statisticsBatch(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>,<a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>());</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>        RealMatrix inputBatch(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>,<a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>());</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>        output.resize(state.size1(),<a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>());</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>        </div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>        <a class="code hl_function" href="classshark_1_1_r_b_m.html#a8fb50f496bfd20e8a3e1cd9573b82ce2" title="Returns the energy function of the RBM.">energy</a>().<a class="code hl_function" href="structshark_1_1_energy.html#a751c81c6de87a9d563d36db38edccb92" title="Calculates the input of the hidden neurons given the state of the visible in a batch-vise fassion.">inputHidden</a>(inputBatch,state);</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span>        <a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>().sufficientStatistics(inputBatch,statisticsBatch,blas::repeat(1.0,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>));</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span> </div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>        <span class="keywordflow">if</span>(m_evalMean){</div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>            noalias(output) = <a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>().mean(statisticsBatch);</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>        }</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>        <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>            <a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>().sample(statisticsBatch,output,0.0,*mpe_rng);</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>        }</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span>    }</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span><span class="comment"></span> </div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span><span class="comment">    ///\brief Evaluates the input by propagating the hidden input to the visible neurons.</span></div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span><span class="comment">    ///@param patterns batch of states of hidden units</span></div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span><span class="comment">    ///@param outputs batch of (expected) states of visible units</span></div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span><span class="comment"></span>    <span class="keywordtype">void</span> evalBackward(<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">BatchInputType</a> <span class="keyword">const</span>&amp; state,<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">BatchOutputType</a>&amp; output)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>        std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = state.size1();</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>        <span class="keyword">typename</span> VisibleType::StatisticsBatch statisticsBatch(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>,<a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>());</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>        RealMatrix inputBatch(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>,<a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>());</div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span>        output.resize(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>,<a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>());</div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>        </div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>        <a class="code hl_function" href="classshark_1_1_r_b_m.html#a8fb50f496bfd20e8a3e1cd9573b82ce2" title="Returns the energy function of the RBM.">energy</a>().<a class="code hl_function" href="structshark_1_1_energy.html#acf73968e06c43cedaf8fede5b2bf7782" title="Calculates the input of the visible neurons given the state of the hidden.">inputVisible</a>(inputBatch,state);</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>        <a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>().sufficientStatistics(inputBatch,statisticsBatch,blas::repeat(1.0,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>));</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>        </div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>        <span class="keywordflow">if</span>(m_evalMean){</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>            noalias(output) = <a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>().mean(statisticsBatch);</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>        }</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>        <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>            <a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>().sample(statisticsBatch,output,0.0,*mpe_rng);</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>        }</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>    }</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span><span class="keyword">public</span>:</div>
<div class="foldopen" id="foldopen00112" data-start="{" data-end="}">
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#ab7e7691d5840fe1a87b9b220e9d9ab47">  112</a></span>    <a class="code hl_function" href="classshark_1_1_r_b_m.html#ab7e7691d5840fe1a87b9b220e9d9ab47">RBM</a>(<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5b791282749a918b7894a9cb01c29a36">randomType</a>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a7ec198cf576079447b2c78661625980b" title="Returns the random number generator associated with this RBM.">rng</a>):mpe_rng(&amp;<a class="code hl_function" href="classshark_1_1_r_b_m.html#a7ec198cf576079447b2c78661625980b" title="Returns the random number generator associated with this RBM.">rng</a>),m_forward(true),m_evalMean(true)</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>    { }</div>
</div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span><span class="comment"></span> </div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span><span class="comment">    /// \brief From INameable: return the class name.</span></div>
<div class="foldopen" id="foldopen00116" data-start="{" data-end="}">
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#ae2d7c8d3c93a4d8e01a066793d5f2cb5">  116</a></span><span class="comment"></span>    std::string <a class="code hl_function" href="classshark_1_1_r_b_m.html#ae2d7c8d3c93a4d8e01a066793d5f2cb5" title="From INameable: return the class name.">name</a>()<span class="keyword"> const</span></div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span><span class="keyword">    </span>{ <span class="keywordflow">return</span> <span class="stringliteral">&quot;RBM&quot;</span>; }</div>
</div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span><span class="comment"></span> </div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span><span class="comment">    ///\brief Returns the total number of parameters of the model.</span></div>
<div class="foldopen" id="foldopen00120" data-start="{" data-end="}">
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a7db1411301e34ef5fb6c1ab98dfbfed4">  120</a></span><span class="comment"></span>    std::size_t <a class="code hl_function" href="classshark_1_1_r_b_m.html#a7db1411301e34ef5fb6c1ab98dfbfed4" title="Returns the total number of parameters of the model.">numberOfParameters</a>()<span class="keyword">const </span>{</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>        std::size_t parameters = <a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>()*<a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>();</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>        parameters += m_hiddenNeurons.numberOfParameters();</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>        parameters += m_visibleNeurons.numberOfParameters();</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>        <span class="keywordflow">return</span> parameters;</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>    }</div>
</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>    <span class="comment"></span></div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span><span class="comment">    ///\brief Returns the parameters of the Model as parameter vector.</span></div>
<div class="foldopen" id="foldopen00128" data-start="{" data-end="}">
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#aef829473dfa3b3c8bce134aba6fd7420">  128</a></span><span class="comment"></span>    RealVector <a class="code hl_function" href="classshark_1_1_r_b_m.html#aef829473dfa3b3c8bce134aba6fd7420" title="Returns the parameters of the Model as parameter vector.">parameterVector</a> ()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>        <span class="keywordflow">return</span>  to_vector(m_weightMatrix) </div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>        | m_hiddenNeurons.parameterVector() </div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>        | m_visibleNeurons.parameterVector();</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>    };</div>
</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span><span class="comment"></span> </div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span><span class="comment">    ///\brief Sets the parameters of the model.</span></div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="comment">    /// @param newParameters vector of parameters  </span></div>
<div class="foldopen" id="foldopen00137" data-start="{" data-end="}">
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a4412f9b10e320b1db350284a94a4b34d">  137</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a4412f9b10e320b1db350284a94a4b34d" title="Sets the parameters of the model.">setParameterVector</a>(<span class="keyword">const</span> RealVector&amp; newParameters) {</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span>        std::size_t endW = <a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>()*<a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>();</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>        std::size_t endH = endW + m_hiddenNeurons.numberOfParameters();</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>        std::size_t endV = endH + m_visibleNeurons.numberOfParameters();</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>        noalias(to_vector(m_weightMatrix)) = subrange(newParameters,0,endW);</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>        m_hiddenNeurons.setParameterVector(subrange(newParameters,endW,endH));</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>        m_visibleNeurons.setParameterVector(subrange(newParameters,endH,endV));     </div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>    }</div>
</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>    <span class="comment"></span></div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span><span class="comment">    ///\brief Creates the structure of the RBM.</span></div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span><span class="comment">    ///@param hiddenNeurons number of hidden neurons.</span></div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span><span class="comment">    ///@param visibleNeurons number of visible neurons.</span></div>
<div class="foldopen" id="foldopen00150" data-start="{" data-end="}">
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a9ef4cbc58af54464387b84111938dd12">  150</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a9ef4cbc58af54464387b84111938dd12" title="Creates the structure of the RBM.">setStructure</a>(std::size_t <a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>,std::size_t <a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>){</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>        m_weightMatrix.resize(<a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>,<a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>);</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>        m_weightMatrix.clear();</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span>        </div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>        m_hiddenNeurons.resize(<a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>);</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>        m_visibleNeurons.resize(<a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>);</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>    }</div>
</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>    <span class="comment"></span></div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span><span class="comment">    ///\brief Returns the layer of hidden neurons.</span></div>
<div class="foldopen" id="foldopen00159" data-start="{" data-end="}">
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f">  159</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a1b20cbe042d3ac817fbf26c562e5b277" title="type of the hidden layer">HiddenType</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a2c69b9101da84089ff38a8eb3e6b4a9f" title="Returns the layer of hidden neurons.">hiddenNeurons</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span>        <span class="keywordflow">return</span> m_hiddenNeurons;</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span><span class="comment">    ///\brief Returns the layer of hidden neurons.</span></div>
<div class="foldopen" id="foldopen00163" data-start="{" data-end="}">
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#ad185b821633258df02fe62c3d5e08a54">  163</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a1b20cbe042d3ac817fbf26c562e5b277" title="type of the hidden layer">HiddenType</a>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#ad185b821633258df02fe62c3d5e08a54" title="Returns the layer of hidden neurons.">hiddenNeurons</a>(){</div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span>        <span class="keywordflow">return</span> m_hiddenNeurons;</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span><span class="comment">    ///\brief Returns the layer of visible neurons.</span></div>
<div class="foldopen" id="foldopen00167" data-start="{" data-end="}">
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45">  167</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5e271a43da1f3c33db74235402d7a84b" title="type of the visible layer">VisibleType</a>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a5d79874854c30c34ff7d13a62bbf6b45" title="Returns the layer of visible neurons.">visibleNeurons</a>(){</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>        <span class="keywordflow">return</span> m_visibleNeurons;</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span><span class="comment">    ///\brief Returns the layer of visible neurons.</span></div>
<div class="foldopen" id="foldopen00171" data-start="{" data-end="}">
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a579f3f64d7eb907a501c91a1907f6133">  171</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5e271a43da1f3c33db74235402d7a84b" title="type of the visible layer">VisibleType</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a579f3f64d7eb907a501c91a1907f6133" title="Returns the layer of visible neurons.">visibleNeurons</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno">  172</span>        <span class="keywordflow">return</span> m_visibleNeurons;</div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>    }</div>
</div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>    <span class="comment"></span></div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span><span class="comment">    ///\brief Returns the weight matrix connecting the layers.</span></div>
<div class="foldopen" id="foldopen00176" data-start="{" data-end="}">
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a84024ce828171989645feca12095c3cd">  176</a></span><span class="comment"></span>    RealMatrix&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a84024ce828171989645feca12095c3cd" title="Returns the weight matrix connecting the layers.">weightMatrix</a>(){</div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span>        <span class="keywordflow">return</span> m_weightMatrix;</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span><span class="comment">    ///\brief Returns the weight matrix connecting the layers.</span></div>
<div class="foldopen" id="foldopen00180" data-start="{" data-end="}">
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a09fbb9d2b6b4dddd151ec65ca278acc7">  180</a></span><span class="comment"></span>    RealMatrix <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a09fbb9d2b6b4dddd151ec65ca278acc7" title="Returns the weight matrix connecting the layers.">weightMatrix</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>        <span class="keywordflow">return</span> m_weightMatrix;</div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span>    }</div>
</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span>    <span class="comment"></span></div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span><span class="comment">    ///\brief Returns the energy function of the RBM.</span></div>
<div class="foldopen" id="foldopen00185" data-start="{" data-end="}">
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a8fb50f496bfd20e8a3e1cd9573b82ce2">  185</a></span><span class="comment"></span>    <a class="code hl_struct" href="structshark_1_1_energy.html" title="The Energy function determining the Gibbs distribution of an RBM.">EnergyType</a> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a8fb50f496bfd20e8a3e1cd9573b82ce2" title="Returns the energy function of the RBM.">energy</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a9e64a75e314d39c06b298f348f4edb27" title="Type of the energy function.">EnergyType</a>(*<span class="keyword">this</span>);</div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>    }</div>
</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>    <span class="comment"></span></div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span><span class="comment">    ///\brief Returns the random number generator associated with this RBM.</span></div>
<div class="foldopen" id="foldopen00190" data-start="{" data-end="}">
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a7ec198cf576079447b2c78661625980b">  190</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a5b791282749a918b7894a9cb01c29a36">randomType</a>&amp; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a7ec198cf576079447b2c78661625980b" title="Returns the random number generator associated with this RBM.">rng</a>(){</div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span>        <span class="keywordflow">return</span> *mpe_rng;</div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>    }</div>
</div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>    <span class="comment"></span></div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span><span class="comment">    ///\brief Sets the type of evaluation, eval will perform.</span></div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span><span class="comment">    ///Eval performs its operation based on the state of this function.</span></div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span><span class="comment">    ///There are two ways to pass data through an rbm: either forward, setting the states of the</span></div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span><span class="comment">    ///visible neurons and sample the hidden states or backwards, where the state of the hidden is fixed and the visible</span></div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span><span class="comment">    ///are sampled. </span></div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span><span class="comment">    ///Instead of the state of the hidden/visible, one often wants the mean of the state \f$ E_{p(h|v)}\left(h\right)\f$. </span></div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span><span class="comment">    ///By default, the RBM uses the forward evaluation and returns the mean of the state</span></div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span><span class="comment">    ///@param forward whether the forward view should be used false=backwards</span></div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span><span class="comment">    ///@param evalMean whether the mean state should be returned. false=a sample is returned</span></div>
<div class="foldopen" id="foldopen00205" data-start="{" data-end="}">
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#ad94533d058118a9a0ba544b4c38d9517">  205</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#ad94533d058118a9a0ba544b4c38d9517" title="Sets the type of evaluation, eval will perform.">evaluationType</a>(<span class="keywordtype">bool</span> forward,<span class="keywordtype">bool</span> evalMean){</div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span>        m_forward = forward;</div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>        m_evalMean = evalMean;</div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>    }</div>
</div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>    </div>
<div class="foldopen" id="foldopen00210" data-start="{" data-end="}">
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a38b0902cc476633d87d332220d13e9a0">  210</a></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a38b0902cc476633d87d332220d13e9a0" title="Returns the shape of the output.">outputShape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span>        <span class="keywordflow">if</span>(m_forward){</div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span>            <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>();</div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span>        }<span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno">  214</span>            <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>();</div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span>        }</div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span>    }</div>
</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span>    </div>
<div class="foldopen" id="foldopen00218" data-start="{" data-end="}">
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a51a624959ff348a01150a8ea654709ff">  218</a></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a51a624959ff348a01150a8ea654709ff" title="Returns the expected shape of the input.">inputShape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span>        <span class="keywordflow">if</span>(m_forward){</div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span>            <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>();</div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span>        }<span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span>            <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>();</div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span>        }</div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span>    }</div>
</div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span>    </div>
<div class="foldopen" id="foldopen00226" data-start="{" data-end="}">
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a5e0f8d86ec292aeb2cd89525750a5079">  226</a></span>    boost::shared_ptr&lt;State&gt; <a class="code hl_function" href="classshark_1_1_r_b_m.html#a5e0f8d86ec292aeb2cd89525750a5079" title="Creates an internal state of the model.">createState</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span>        <span class="keywordflow">return</span> boost::shared_ptr&lt;State&gt;(<span class="keyword">new</span> <a class="code hl_struct" href="structshark_1_1_empty_state.html" title="Default State of an Object which does not need a State.">EmptyState</a>());</div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span>    }</div>
</div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span>    <span class="comment"></span></div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span><span class="comment">    ///\brief Passes information through/samples from an RBM in a forward or backward way. </span></div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span><span class="comment">    ///Eval performs its operation based on the given evaluation type.</span></div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span><span class="comment">    ///There are two ways to pass data through an RBM: either forward, setting the states of the</span></div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span><span class="comment">    ///visible neurons and sample the hidden states or backwards, where the state of the hidden is fixed and the visible</span></div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span><span class="comment">    ///are sampled. </span></div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span><span class="comment">    ///Instead of the state of the hidden/visible, one often wants the mean of the state \f$ E_{p(h|v)}\left(h\right)\f$. </span></div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span><span class="comment">    ///By default, the RBM uses the forward evaluation and returns the mean of the state,</span></div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span><span class="comment">    ///but other evaluation modes can be set by evaluationType().</span></div>
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno">  239</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno">  240</span><span class="comment">    ///@param patterns the batch of (visible or hidden) inputs</span></div>
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno">  241</span><span class="comment">    ///@param outputs the batch of (visible or hidden) outputs </span></div>
<div class="foldopen" id="foldopen00242" data-start="{" data-end="}">
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a25713d2a3e7881d18fe7d767e0021da9">  242</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a25713d2a3e7881d18fe7d767e0021da9" title="Passes information through/samples from an RBM in a forward or backward way.">eval</a>(<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">BatchInputType</a> <span class="keyword">const</span>&amp; patterns,<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">BatchOutputType</a>&amp; outputs)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno">  243</span>        <span class="keywordflow">if</span>(m_forward){</div>
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno">  244</span>            evalForward(patterns,outputs);</div>
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno">  245</span>        }</div>
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno">  246</span>        <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno">  247</span>            evalBackward(patterns,outputs);</div>
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno">  248</span>        }</div>
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno">  249</span>    }</div>
</div>
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno">  250</span> </div>
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno">  251</span> </div>
<div class="foldopen" id="foldopen00252" data-start="{" data-end="}">
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a4ba01d8ede9a53e1771471dc62e74a74">  252</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a4ba01d8ede9a53e1771471dc62e74a74" title="Standard interface for evaluating the response of the model to a batch of patterns.">eval</a>(<a class="code hl_typedef" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">BatchInputType</a> <span class="keyword">const</span>&amp; patterns, <a class="code hl_typedef" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">BatchOutputType</a>&amp; outputs, <a class="code hl_struct" href="structshark_1_1_state.html" title="Represents the State of an Object.">State</a>&amp; state)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno">  253</span>        <a class="code hl_function" href="classshark_1_1_r_b_m.html#a25713d2a3e7881d18fe7d767e0021da9" title="Passes information through/samples from an RBM in a forward or backward way.">eval</a>(patterns,outputs);</div>
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno">  254</span>    }</div>
</div>
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno">  255</span>    <span class="comment"></span></div>
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno">  256</span><span class="comment">    ///\brief Calculates the input of the hidden neurons given the state of the visible in a batch-vise fassion.</span></div>
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno">  257</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno">  258</span><span class="comment">    ///@param inputs the batch of vectors the input of the hidden neurons is stored in</span></div>
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno">  259</span><span class="comment">    ///@param visibleStates the batch of states of the visible neurons</span></div>
<div class="foldopen" id="foldopen00260" data-start="{" data-end="}">
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a87ff1500124f108b836beebc4ee0eeb4">  260</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a87ff1500124f108b836beebc4ee0eeb4" title="Calculates the input of the hidden neurons given the state of the visible in a batch-vise fassion.">inputHidden</a>(RealMatrix&amp; inputs, RealMatrix <span class="keyword">const</span>&amp; visibleStates)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno">  261</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(visibleStates.size1() == inputs.size1());</div>
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno">  262</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(inputs.size2() == m_hiddenNeurons.size());</div>
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno">  263</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>( visibleStates.size2() == m_visibleNeurons.size());</div>
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno">  264</span>        </div>
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno">  265</span>        noalias(inputs) = prod(m_visibleNeurons.phi(visibleStates),trans(m_weightMatrix));</div>
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno">  266</span>    }</div>
</div>
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno">  267</span> </div>
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno">  268</span><span class="comment"></span> </div>
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno">  269</span><span class="comment">    ///\brief Calculates the input of the visible neurons given the state of the hidden.</span></div>
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno">  270</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno">  271</span><span class="comment">    ///@param inputs the vector the input of the visible neurons is stored in</span></div>
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno">  272</span><span class="comment">    ///@param hiddenStates the state of the hidden neurons</span></div>
<div class="foldopen" id="foldopen00273" data-start="{" data-end="}">
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#ab6140a0df931943c1c26bc07065a5565">  273</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#ab6140a0df931943c1c26bc07065a5565" title="Calculates the input of the visible neurons given the state of the hidden.">inputVisible</a>(RealMatrix&amp; inputs, RealMatrix <span class="keyword">const</span>&amp; hiddenStates)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno">  274</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(hiddenStates.size1() == inputs.size1());</div>
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno">  275</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(inputs.size2() == m_visibleNeurons.size());</div>
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno">  276</span>        </div>
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno">  277</span>        noalias(inputs) = prod(m_hiddenNeurons.phi(hiddenStates),m_weightMatrix);</div>
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno">  278</span>    }</div>
</div>
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno">  279</span>    </div>
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno">  280</span>    <span class="keyword">using </span><a class="code hl_function" href="classshark_1_1_abstract_model.html#ac7edef74da55322b6aef0ba65b08592d" title="Standard interface for evaluating the response of the model to a batch of patterns.">base_type::eval</a>;</div>
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno">  281</span>    </div>
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno">  282</span>    <span class="comment"></span></div>
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno">  283</span><span class="comment">    ///\brief Returns the number of hidden Neurons.</span></div>
<div class="foldopen" id="foldopen00284" data-start="{" data-end="}">
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240">  284</a></span><span class="comment"></span>    std::size_t <a class="code hl_function" href="classshark_1_1_r_b_m.html#aff68280f2b354df64b4ac311bcd0a240" title="Returns the number of hidden Neurons.">numberOfHN</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno">  285</span>        <span class="keywordflow">return</span> m_hiddenNeurons.size();</div>
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno">  286</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno">  287</span><span class="comment">    ///\brief Returns the number of visible Neurons.</span></div>
<div class="foldopen" id="foldopen00288" data-start="{" data-end="}">
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c">  288</a></span><span class="comment"></span>    std::size_t <a class="code hl_function" href="classshark_1_1_r_b_m.html#aa2832c9073247890ae6f17285cc5056c" title="Returns the number of visible Neurons.">numberOfVN</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno">  289</span>        <span class="keywordflow">return</span> m_visibleNeurons.size();</div>
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno">  290</span>    }</div>
</div>
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno">  291</span>    <span class="comment"></span></div>
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno">  292</span><span class="comment">    /// \brief Reads the network from an archive.</span></div>
<div class="foldopen" id="foldopen00293" data-start="{" data-end="}">
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a1f347deac6a9d06e1ae485dfa0fd276e">  293</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a1f347deac6a9d06e1ae485dfa0fd276e" title="Reads the network from an archive.">read</a>(<a class="code hl_typedef" href="namespaceshark.html#ada68729491840669e47c8ad42282424f" title="Type of an archive to read from.">InArchive</a>&amp; archive){</div>
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno">  294</span>        archive &gt;&gt; m_weightMatrix;</div>
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno">  295</span>        archive &gt;&gt; m_hiddenNeurons;</div>
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno">  296</span>        archive &gt;&gt; m_visibleNeurons;</div>
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno">  297</span>        </div>
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno">  298</span>        <span class="comment">//serialization of the rng is a bit...complex</span></div>
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno">  299</span>        <span class="comment">//let&#39;s hope that we can remove this hack one time. But we really can&#39;t ignore the state of the rng.</span></div>
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno">  300</span>        std::string str;</div>
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno">  301</span>        archive&gt;&gt; str;</div>
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno">  302</span>        std::stringstream stream(str);</div>
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno">  303</span>        stream&gt;&gt; *mpe_rng;</div>
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno">  304</span>    }</div>
</div>
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno">  305</span><span class="comment"></span> </div>
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno">  306</span><span class="comment">    /// \brief Writes the network to an archive.</span></div>
<div class="foldopen" id="foldopen00307" data-start="{" data-end="}">
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno"><a class="line" href="classshark_1_1_r_b_m.html#a86fc20140fb2838b0e2dbbdee0a36650">  307</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_r_b_m.html#a86fc20140fb2838b0e2dbbdee0a36650" title="Writes the network to an archive.">write</a>(<a class="code hl_typedef" href="namespaceshark.html#af4f8eb8e9618f5236b71bbcb12b8a524" title="Type of an archive to write to.">OutArchive</a>&amp; archive)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno">  308</span>        archive &lt;&lt; m_weightMatrix;</div>
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno">  309</span>        archive &lt;&lt; m_hiddenNeurons;</div>
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno">  310</span>        archive &lt;&lt; m_visibleNeurons;</div>
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno">  311</span>        </div>
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno">  312</span>        std::stringstream stream;</div>
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno">  313</span>        stream &lt;&lt;*mpe_rng;</div>
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno">  314</span>        std::string str = stream.str();</div>
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno">  315</span>        archive &lt;&lt;str;</div>
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno">  316</span>    }</div>
</div>
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno">  317</span> </div>
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno">  318</span>};</div>
</div>
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno">  319</span> </div>
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno">  320</span>}</div>
<div class="line"><a id="l00321" name="l00321"></a><span class="lineno">  321</span> </div>
<div class="line"><a id="l00322" name="l00322"></a><span class="lineno">  322</span><span class="preprocessor">#endif</span></div>
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